We find it worthwhile to point out that this scaling is better than one might expect.
Standard results in statistical learning theory [1]}, [2]} usually yield a data size of order \(\log (|M^p_{4 \epsilon }(\operatorname{{\mathcal {F}}}_f)|) / \epsilon ^2\) , which is worse than our result by an additional \(1/\epsilon \)  factor.
